Challenging the Barriers to High Performance Computing in the Cloud

Cloud computing helps democratize High Performance Computing (HPC) by placing powerful computational capabilities in the hands of more researchers, engineers, and organizations who may lack access to sufficient on-premises infrastructure. The cloud’s flexibility and scalability offer virtually unlimited capacity, eliminating wait times and long job queues. Access to new and evolving services and applications make it easy to evolve and modernize workflows, like incorporating Artificial Intelligence (AI) with HPC. With HPC in the cloud, organizations only pay for the capacity they use, and there’s no risk of on-premises infrastructure becoming obsolete or poorly utilized. In addition, cloud-based services enable innovation without constraints by delivering faster results and improved flexibility. Amazon Web Services (AWS) gives organizations the power to create HPC clusters on demand, instead of waiting for equipment to be built—helping drive business insights and organization productivity.

Despite its advantages, some organizations remain hesitant to move their HPC workloads to the cloud, due to questions about cost, security and performance. With today’s clouds, these assertions are outdated and generally inaccurate. HPC on AWS, powered by Intel® Xeon® Scalable processors, offers the most elastic, scalable cloud infrastructure to run HPC applications, and the range of services makes it easier than ever to get started quickly, securely, and cost-effectively.

Cost and Cost Management

For many organizations, the cost of running HPC in the cloud is a major concern. In a recent market survey conducted by a third party for AWS, almost half (49%) of participants said cost and cost-management were barriers.  When considering the cost of cloud-based HPC systems, organizations should note that in many cases a basic TCO analysis often does not tell the whole story. Demand for on-premises HPC resources often exceeds capacity and lost productivity due to an over utilized system has massive implications for organizations that place high value on the pace of innovation. Moving HPC workloads to the cloud also eliminates the need for periodic technology and infrastructure refresh cycles every three to five years, ensuring that innovation continues at a rapid pace.

AWS delivers an integrated suite of services that provides everything needed to build and manage HPC clusters in the cloud, simply and cost-effectively. There are no upfront capital expenditures or lengthy procurement cycles, and the only cost is for capacity used. It offers flexible pricing models that provide significant cost savings for time-flexible, stateless workloads. AWS constantly delivers new services and features, like 2nd generation Intel Xeon Scalable processors with Intel® Deep Learning Boost (Intel DL Boost) to enable new capabilities, improved performance, and optimization for all current HPC frameworks. AWS offers cost management and analysis tools such as AWS Cost Explorer and AWS Budgets. Additionally, AWS partners like Ronin have built cost-control models on the platform.

Data Security and Data Governance

Concerns about cloud security are nothing new. Many industries that use HPC heavily have stringent security requirements, and it’s a commonly cited obstacle to cloud-based HPC solutions. 43% of participants in the HPC market survey had concerns about data security and governance, and 42% also listed data privacy. While some perceive security and privacy benefits to on-premises HPC, they don’t account for risk management issues like aging infrastructure that increase the security costs of maintaining compliance, or for expensive regulatory compliance and certifications often required for on-premises solutions. They may not sufficiently account for the complex landscape that security compliance has become and the benefits of a shared responsibility model where AWS helps relieve the customer’s operational burden by operating, managing and controlling the components from the host operating system and virtualization layer down to the physical security of the facilities in which the service operates.

Cloud security is a high priority at AWS and we offer several tools and services to ensure encryption, manage access, and secure regulated workloads. All data is stored in highly secure AWS data centers, and the network architecture is built to meet the requirements of the most risk-sensitive organizations. Additionally, customers maintain ownership and control of all content—they can select which AWS services can process, store and host content, determine where it will be stored, choose its secured state, and manage all access. When a customer uses AWS services, they operate in a shared responsibility environment, where the secure functioning of an application on AWS requires action from both the customer and AWS. All institutions should explain the shared responsibility model to their stakeholders throughout the design, development, testing, and production phases of cloud adoption. Customers are responsible for security IN the cloud. They control and manage the security of their content, applications, systems, and networks. AWS manages security OF the cloud to protect infrastructure and services, maintain operational performance, and meet relevant legal and regulatory requirements.  Intel Xeon  Scalable processor-based AWS instances deliver hardware-enabled security capabilities directly on the silicon to help protect every layer of the compute stack, including hardware, firmware, operating systems, applications, networks, and the cloud. Intel® Threat Detection Technology (Intel® TDT) is also available on 2nd Generation Intel Xeon Scalable processors and delivers hardware-enhanced threat detection.

Data Transfer

Running HPC applications in the cloud starts with moving the required data into the cloud, but this process can be an obstacle for many organizations. The market study found that 41% of those surveyed were concerned about getting data into—and out of—the cloud. Commonly cited data transfer barriers are time and money, but while it may seem easier in the long run to keep data in on-premises HPC infrastructure, the investment in moving data to the cloud is far outweighed by the benefits of more flexible, agile HPC. Moving data and HPC to the cloud improves efficiency by freeing up valuable financial and staff resources, and reduces business risks by storing data in a more resilient, secure environment. In addition, cloud-based HPC enables customers to utilize AI, machine learning and deep learning to mine all the data available from HPC simulations, narrowing the range of simulations required—meaning cheaper, faster HPC workload execution. Since newer, cloud-native HPC applications were designed to perform better on cloud-based elastic infrastructure, improved performance in the cloud can deliver better ROI.


Organizations using High Performance Computing expect high performance—and many still don’t believe the cloud can compete with on-premises data centers. 35% of participants in the market survey mentioned concerns about network performance and inter-connect latencies, and 29% mentioned broader performance concerns. But the belief that the networking speed between compute nodes in the cloud is not fast enough for high performance is outdated. Recent advancements have helped speed up cloud networking and trim latency to the point where all but the most resource-intensive HPC applications run just as well or better on the cloud than on on-premises infrastructure. AWS performance exceeds the needs of almost every HPC use-case in terms of scalability, elasticity and raw performance, and typically delivers better ROI. Elastic Fabric Adapter (EFA) – a network interface for Amazon EC2 instances offers a unique OS bypass networking mechanism to provide a low latency, low-jitter channel for inter-instance communications. This enables tightly coupled HPC or distributed machine learning applications to scale to thousands of cores, so applications run faster.  For a standard CFD simulation, the use of EFA shows a 4x improvement in scaling over using the standard networking for EC2 instances.

Performance Cloud HPC Amazon

In another performance benchmark exercise, Amazon EC2 C5n instances were compared to a mainstream HPC node from a leading on-premises HPC OEM running a standard CFD use case. Engineering simulation software provider ANSYS publishes ANSYS® Fluent® benchmarks of “External Flow Over a Formula-1 Race Car.” This case has around 140-million Hex-core cells and uses the realizable k-epsilon turbulence model as well as the Pressure-based coupled solver and the Least Squares cell-based, pseudo-transient solver. Running the same benchmark using Amazon EC2 C5n instances and Elastic Fabric Adapter is a simple way to benchmark the performance of the solver on AWS and compare it against traditional HPC infrastructure.

The plot below shows the rating of the on-premises OEM’s HPC node and C5n.18xlarge with EFA. ANSYS defines this rating as “the primary metric used to report performance results of the Fluent Benchmarks. It is defined as the number of benchmarks that can be run on a given machine (in sequence) in a 24-hour period. It is computed by dividing the number of seconds in a day (86,400 seconds) by the number of seconds required to run the benchmark. A higher rating means better performance.” 

Amazon HPC Cloud Race Car
The plot shows C5n.18xlarge with EFA got a higher rating up to 2400 cores and is essentially on par up to about 3800 cores.


HPC is an essential function for many industries, but misconceptions about cloud-based HPC may prevent organizations from realizing the benefits of these powerful systems—like quicker time to market, new business insights, unprecedented agility and scalability, and more. When comparing on-premises infrastructure to cloud-based HPC, it’s important to consider factors beyond a simple cost-per-core-hour analysis and look at the holistic business impact. Factors like personnel productivity, cutting-edge technology, and innovation acceleration are critical in the new digital economy—the difference between leading the industry or playing catch-up.

The ability to create customized compute clusters in the AWS cloud enables cost-effective HPC for most business cases, from small research teams to large enterprise organizations. And AWS offers a suite of integrated products and services that keep data private and secure, make it easy to migrate and transfer data, and deliver consistent high performance.  Learn more about HPC on AWS here.

Written by Bala Thekkedath, Global HPC Marketing Lead, Amazon Web Services.